Exploratory factor analysis yields grouping of brain injury biomarkers significantly associated with outcomes in neonatal and pediatric ECMO

In this two-center prospective cohort study of children on ECMO, we assessed a panel of plasma brain injury biomarkers using exploratory factor analysis (EFA) to evaluate their interplay and association with outcomes. Biomarker concentrations were measured daily for the first 3 days of ECMO support in 95 participants. Unfavorable composite outcome was defined as in-hospital mortality or discharge Pediatric Cerebral Performance Category > 2 with decline ≥ 1 point from baseline. EFA grouped 11 biomarkers into three factors. Factor 1 comprised markers of cellular brain injury (NSE, BDNF, GFAP, S100β, MCP1, VILIP-1, neurogranin); Factor 2 comprised markers related to vascular processes (vWF, PDGFRβ, NPTX1); and Factor 3 comprised the BDNF/MMP-9 cellular pathway. Multivariable logistic models demonstrated that higher Factor 1 and 2 scores were associated with higher odds of unfavorable outcome (adjusted OR 2.88 [1.61, 5.66] and 1.89 [1.12, 3.43], respectively). Conversely, higher Factor 3 scores were associated with lower odds of unfavorable outcome (adjusted OR 0.54 [0.31, 0.88]), which is biologically plausible given the role of BDNF in neuroplasticity. Application of EFA on plasma brain injury biomarkers in children on ECMO yielded grouping of biomarkers into three factors that were significantly associated with unfavorable outcome, suggesting future potential as prognostic instruments.

www.nature.com/scientificreports/neurologic etiologies, neurologic injury is one of the main drivers of outcome in the neonatal and pediatric ECMO populations 3 .
The pathophysiology of neurologic injury in critically ill patients requiring ECMO support is complex and not yet well understood.Several neuromonitoring methods are used for early diagnosis of neurologic injury, therapy guidance, avoidance of secondary insults, and neuroprognostication 3,4 .However, it is likely that only multimodal monitoring can capture said complexity.Plasma brain injury biomarkers have been proposed as additions to multimodal monitoring and have been previously shown to be associated with neurologic injury in critically ill children, including those on ECMO support.These include biomarkers of primary structural damage but also of secondary cascade of injury and repair in the brain 7 , such as markers of neuronal injury: neuron-specific enolase (NSE) 8,9 , of neuroregeneration: brain-derived neurotrophic factor (BDNF) 9 , of astrocytic injury: glial fibrillary acidic protein (GFAP) 9,10 and S100β 8,9,11 , and of neuroinflammation: monocyte chemoattractant protein 1 (MCP1) 9 .
In this study, we aimed to assess if use of exploratory factor analysis (EFA) on an expanded panel of brain injury biomarkers previously evaluated in various types of brain injury could lead to better understanding of the interplay of these biomarkers and their association with unfavorable outcomes and abnormal neuroimaging in critically ill children on ECMO support.

Study population
This prospective observational cohort study enrolled neonatal and pediatric patients on ECMO support at two academic, quaternary care, urban, pediatric intensive care units between July 2010 and June 2015.Characteristics of the cohort have been previously described 5 .Informed consent was obtained from all parents within 24 h of ECMO initiation.A total of 99 children were enrolled in the parent study.Of these, 95 subjects had longitudinal blood samples obtained daily during the first 3 days of the ECMO course.Platelet-poor plasma aliquots that had not undergone any freeze-thaw cycles and had been stored at -80 °C in a freezer with continuous temperature monitoring were used for the current study.We collected data from neuroimaging reports of serial head ultrasounds obtained daily during the ECMO course in infants with open anterior fontanel as part of routine clinical protocols at the two participating institutions, and of brain computed tomography (CT) and/or brain magnetic resonance imaging (MRI) studies that were obtained based on clinical indications at the discretion of the clinical team, during the ECMO course and up to six weeks after decannulation.Clinical imaging reports noting abnormal findings were then classified as postasphyxial injury, arterial ischemic stroke, and intracranial hemorrhage, noting that imaging studies frequently detected more than one type of injury.Types of neuroimaging findings and time to first abnormal neuroimaging are presented in Supplemental Table 1.Pediatric Cerebral Performance Category (PCPC) scores at baseline and hospital discharge were ascertained from the medical records locally and in real-time by trained data abstractors who were blinded to biomarker results 31,32 .This study was approved by the Johns Hopkins Medicine and the Children's National Institutional Review Boards at the two participating centers and performed in accordance with relevant guidelines and regulations.

Descriptive analysis of biomarkers
Of all available samples from a given participant, the highest value, or peak, of any given biomarker measured daily for the first 3 days of ECMO support was used for EFA.Biomarkers had right-skewed distributions and were therefore natural log-transformed.Seventy-two of 295 biomarker observations lay above their upper limit of quantification (ULOQ), all related to 5 (GFAP, MCP1, MMP-9, S100β, VILIP-1) of the 11 biomarkers included in the analysis.To utilize EFA, which requires numerical values for all data, we imputed values for these 72 observations using truncated log-normal distributions for each biomarker.Specifically, we fit a normal distribution to the observed data, extrapolated the curve above the ULOQ, and drew values randomly from the distribution above the ULOQ. www.nature.com/scientificreports/

EFA methods
We used EFA to detect combinations of biomarkers that indicated unique processes agnostic to covariates and outcomes of interest.EFA identifies groups of markers that are highly correlated and thus likely to reflect the same process.Log-transformed biomarker values (observed and imputed) were standardized to create distributions with a mean of 0 and a standard deviation of 1. Principal components analysis was used to produce proportion criteria and create a scree plot used to reduce the brain injury biomarkers to an optimal number of factors that retained the most amount of total variance in the original variables.The factors were derived using generalized weighted least squares methods and oblique rotation on the peak measurements to transform the factors and obtain factor loadings, which represent the strength and direction of the relationship between the biomarkers and the underlying (latent) relationships.For factor interpretation, only biomarkers with factor loadings ≥ 0.3 were considered; however, the final factor scores were based on all variables.The standardized factor scores for each participant were derived using the tenBerge regression scoring method, which preserves the correlation between factors for an oblique solution 33 .
The factors were then included as dependent variables in linear regression models to evaluate associations with clinical characteristics including participant age, sex, and ECMO indication.Next, the factors were included as independent variables in multivariable logistic regression models.The primary outcome for the first set of models was a composite unfavorable outcome, defined as in-hospital mortality or decline in neurofunctional status defined as discharge PCPC > 2 with decline ≥ 1 from baseline PCPC 5 .The secondary outcome for the second set of logistic models was new abnormal neuroimaging during the ECMO course or within 6 weeks of ECMO decannulation, evaluated among the subset of patients with available neuroimaging.These logistic regression models included each factor separately and summarized the association between each factor and unfavorable outcome, unadjusted and adjusted for age, sex, and ECMO indication.All analyses were performed using R 3.6.0(R Core Team, Vienna, Austria).

Results
Demographic and clinical characteristics of the parent cohort (n = 99) have been previously described 5 .Summary characteristics of the 95 participants included in this analysis are presented in Table 1.www.nature.com/scientificreports/Supplemental Fig. 1 displays the distribution of daily plasma levels of each biomarker during the first 3 days of ECMO support.The distributions of peak plasma biomarker levels are summarized in Supplemental Table 2, which also includes counts and frequencies of biomarker levels above the ULOQ which occurred in 5 biomarkers (GFAP, MCP1, MMP-9, S100β, and VILIP-1).These counts above the ULOQ correspond to the 72 observations that were imputed using the log-normal models shown in Supplemental Fig. 2.

Marker
The distributions of all three brain injury biomarker factor scores by unfavorable versus favorable outcome are graphically displayed in Fig. 1.These distributions indicate that an unfavorable outcome had higher median factor 1 and 2 scores compared to a favorable outcome (+ 0.39 versus -0.52, p < 0.001, and + 0.19 versus -0.22, p = 0.033, respectively).Conversely, lower median factor 3 scores were seen in unfavorable outcomes compared to favorable outcomes (-0.09 versus + 0.44, p = 0.008).
Table 5 presents results from multivariable logistic regression analyses where the composite unfavorable outcome was the dependent variable, and each brain injury biomarker factor score was the exposure of interest in separate models.Brain injury factors 1 and 2 were associated with higher odds of unfavorable outcome (adjusted OR 2.88, 95% CI 1.61-5.66,and adjusted OR 1.89, 95% CI 1.12-3.43,respectively), while brain injury factor 3 was associated with lower odds of unfavorable outcome (adjusted OR 0.54, 95% CI 0.31-0.88).The results of the full multivariable logistic regression models are presented in Supplemental Table 3.   www.nature.com/scientificreports/Among the subset of 84 participants who had neuroimaging studies completed during ECMO or within 6 weeks after ECMO decannulation, factor 1 was associated with higher odds of abnormal neuroimaging (adjusted OR 2.38, 95% CI 1. 38-4.45).Factors 2 and 3 were not significantly associated with abnormal neuroimaging.The results of these multivariable logistic regression models are presented in Supplemental Table 4.Of note, abnormal neuroimaging was not statistically associated with the composite primary outcome, unadjusted (OR 1.80, 95% CI 0.76-4.37)or when adjusting for age, sex, and ECMO indication (adjusted OR 1.45, 95% CI 0.56-3.80).

Discussion
In this two-center prospective observational study of 95 neonatal and pediatric patients on ECMO, we found that 11 circulating biomarkers could be grouped via EFA as a data reduction technique.Specifically, biomarker levels clustered together in three distinct brain injury factors that are biologically plausible based on what is currently known about originating cells and function of each of the biomarkers studied.More importantly, the results indicate that these factors were associated with unfavorable outcome at hospital discharge and new abnormal neuroimaging during or within 6 weeks after ECMO decannulation.
Brain injury factor 1 grouped the following biomarkers: GFAP, S100β, MCP1, NSE, BDNF, VILIP-1, and NRGN.This group encompasses biomarkers of cellular brain injury: neuronal injury, astrocytic injury, and neuroinflammation.To first address markers of neuronal injury, NSE is a glycolytic enzyme localized mostly in neuronal cytoplasm.It has been previously associated with unfavorable outcomes after pediatric cardiac arrest 34 .BDNF is a member of the neurotrophins family of growth factors and mediates neuronal growth, differentiation, regeneration, and survival.It has been implicated in providing neuroplasticity and neuroprotection through reduction in secondary brain injury.BDNF has been associated with pediatric traumatic brain injury (TBI) 35 , favorable outcomes in neonatal hypoxic-ischemic encephalopathy (HIE) 36,37 , and decreased functional impairment in pediatric neurocritical illness 38 .Next, to address markers of astrocytic injury, GFAP is a cytoskeletal filament protein found in mature astrocytes, and its expression is increased during reactive astrogliosis after neurologic injury 39 .It has been shown to predict neurologic injury and outcomes in pediatric patients on cardiopulmonary bypass 40,41 , in pediatric patients with sickle cell disease 42 and severe TBI 43 , and in HIE 37,44,45 .S100β is a calcium-binding protein localized predominately in the cytoplasm of astrocytes and involved in neuronal growth and survival 12,48 and has been associated with unfavorable outcome after pediatric cardiac arrest 34 and in neonatal HIE 46 .Finally, to address neuroinflammation, MCP1 is a small cytokine in the CC chemokine family that plays a key role in recruiting immune factors and cells to sites of inflammation.In the central nervous system, it is found in neurons, astrocytes, microglia, and infiltrating macrophages and thus involved in acute neuroinflammation, neuronal injury and death.MCP1 has been shown to be elevated after neonatal HIE 47 .These five biomarkers (GFAP, S100β, MCP1, NSE, BDNF) have all been previously studied in pediatric ECMO.GFAP, S100β, NSE and MCP1 have been associated with neurologic injury and unfavorable outcomes in pediatric ECMO 9,48 .NSE has also been associated with abnormal neuroimaging in these studies 9 .BDNF's neuroprotective factors have also been previously investigated in pediatric ECMO, but no studies have found associations with survival, outcomes, or neuroimaging 9 .Together, these five biomarkers represent three major categories of neurologic injury pathophysiology-neuronal injury, astrocytic injury, and neuroinflammation-and thus it is fitting for them to be agnostically grouped into one factor.
Two less studied biomarkers, VILIP-1 and NRGN, were also grouped into brain injury factor 1. VILIP-1 is a neuronal calcium sensor protein that has been studied in adult neurodegenerative diseases 49 , stroke 14 , and TBI 13 .The only clinical study in pediatrics found that serum and cerebrospinal fluid levels of VILIP-1 were associated with acute encephalopathy with biphasic seizures and late reduced diffusion 50 .NRGN is a brain-specific postsynaptic calmodulin-binding protein involved in the protein kinase C signaling pathway.Elevated levels have been observed in children with sickle cell disease and stroke 51 and associated with worse neonatal HIE grades and developmental outcomes 37 .The addition of these two biomarkers with more well-established markers of brain injury in one grouped factor suggests that they may warrant further investigation in pediatric brain injury.
The second brain injury factor grouped: vWF, PDGFRβ, and NPTX1.Interestingly, two of the three markers are involved in vascular processes (vWF and PDGFRβ).vWF is a glycoprotein integrally involved in hemostasis through platelet and collagen adhesion and the intrinsic coagulation cascade.It has been previously studied as a marker of endothelial activation and injury in adults with TBI with mixed results [22][23][24] .PDGFRβ is a growth factor receptor that is released with pericyte damage and thus has been used as an indicator of microvascular injury and NPTX1 is a neuronal pentraxin protein preferentially secreted at excitatory synapses and has a role in regulating mitochondria-driven neuronal death in hypoxic-ischemic animal models [25][26][27][28] .None of these three markers have been previously studied in pediatric neurologic injury or critical illness.However, given the association with unfavorable outcomes in this study, they may warrant further investigation into vascular-related pathophysiology in pediatric brain injury.Brain injury factor 3 grouped MMP-9 and BDNF.This is fitting as BDNF has been shown to upregulate MMP-9, a proteinase involved in extracellular matrix degradation, in terms of expression and enzymatic activity 52 .In turn, MMP-9 helps convert pro-BDNF to its activated form.MMP-9 has been previously associated in adult ischemic stroke severity, lesion volume, and hemorrhagic conversion [15][16][17][18] .It has not been as well studied in pediatrics, though elevated levels have been found in neonatal encephalopathy 19 and in neuroinflammatory conditions 53 .This factor's association with lower levels of unfavorable neurologic outcomes in neonatal and pediatric ECMO is supported by the previously discussed neuroprotective properties of BDNF.Interestingly, this suggested neuroprotective property of MMP-9 stands in contrast to previously demonstrated pathogenic properties of other proteases, such as calpain, in many neuropathologies including neonatal encephalopathy [54][55][56] .Additionally, the agnostic grouping of these two biomarkers involved in the same signaling pathway supports that EFA did in fact group combinations that indicate a unique pathophysiologic process.
In summary, EFA agnostically grouped 11 biomarkers into three factors that have compelling shared properties and appear to cluster together, with factor 1 represented by markers of cellular injury, factor 2 represented by markers of microvascular injury, and factor 3 represented by the BDNF and MMP-9 cellular pathway.This study provides insight into a diverse set of biomarkers that have had varying degrees of prior investigation in neonatal and pediatric ECMO and critical illness.For GFAP, S100β, and NSE, we support previously published associations with outcomes in pediatric ECMO.While BDNF and its neuroprotective role have been previously demonstrated, this is the first study to support the role in neonatal and pediatric ECMO.Additionally, we newly describe associations of VILIP-1, NRGN, vWF, PDGFRβ, and MMP-9, which have only been previously studied in infant, pediatric, or adult brain injury and not in neonatal and pediatric ECMO.We also newly describe clinical associations of NPTX1, which has only been previously studied in in vitro and animal models of brain injury.The agnostic grouping suggests that further investigations into clinical or biochemical associations of biomarkers within each factor may be of interest.
This study had several limitations.First, in our study population prior to ECMO, 20% had a pre-existing neurologic diagnosis, 40% had cardiac arrest, and 21% of children with available neuroimaging had acute abnormal findings 5 .Given this high prevalence of pre-ECMO neurologic conditions, it is difficult to specifically attribute these biomarker patterns to neurologic injury in critical illness versus neurologic injury on ECMO.Additionally, in this study, neuroimaging was obtained based on clinical indications and protocols, with head ultrasounds obtained daily for infants and brain CTs obtained when the clinical team had concerns for an acute neurological event.Given that neuroimaging cannot be consistently captured in a standardized manner in this patient population, the exact timing of an acute neurological event cannot be ascertained, with imaging lagging the actual time of onset of the event.Also, for this reason, abnormal neuroimaging is generally deemed not informative as a primary outcome; it was thus treated as a secondary outcome in our study.Furthermore, in the neonatal and pediatric ECMO population, it has been shown that abnormal neuroimaging findings during ECMO have limited associations with long-term neurodevelopmental outcomes in survivors 3 .Lastly, the definition of unfavorable outcome based on PCPC lacks granularity, however ongoing and future studies of blood-based biomarkers will continue to evaluate long-term outcomes as they relate to specific patterns of injury during critical illness with ECMO support.

Conclusions
In this two-center prospective observational study of neonatal and pediatric ECMO, we found that 11 circulating biomarkers could be grouped via EFA to suggest three brain injury factors.The first brain injury factor grouped markers of cellular brain injury.Higher levels were associated with unfavorable survival and neurofunctional outcomes as well as with new abnormal neuroimaging.The second brain injury factor grouped markers related to vascular processes.Higher levels were also associated with unfavorable outcome.Lastly, the third brain injury factor grouped the BDNF and MMP-9 cellular pathway.This pathway was associated with neuroprotective properties, with lower levels associated with unfavorable outcome.

Figure 1 .
Figure 1.Distributions of the three brain injury biomarker factors by outcome (n = 95).The black plots show those with favorable outcome (n = 43), and the red plots show those with unfavorable outcome (n = 52).Wilcoxon rank sum comparisons between factor scores for favorable versus unfavorable outcomes rendered: p < 0.001 for Factor 1, p = 0.033 for Factor 2, and p = 0.008 for Factor 3.

Table 1 .
Demographic and clinical characteristics of children supported on ECMO a .ECMO, extracorporeal membrane oxygenation, PCPC, Pediatric Cerebral Performance Category, HUS, head ultrasound, CT, computed tomography, MRI, magnetic resonance imaging.